Digital encoding of various source signals has become increasingly important over the last decades as digital signal representation and communication increasingly has replaced analogue representation and communication. Continuous research and development is ongoing in how to improve the quality that can be obtained from encoded images and video sequences while at the same time keeping the data rate to acceptable levels.
An important factor for perceived image quality is the dynamic range that can be reproduced when an image is displayed. However, conventionally, the dynamic range of reproduced images has tended to be substantially reduced in relation to normal vision. Indeed, luminance levels encountered in the real world span a dynamic range as large as 14 orders of magnitude, varying from a moonless night to staring directly into the sun. Instantaneous luminance dynamic range and the corresponding human visual system response can fall between 10.000:1 and 100.000:1 on sunny days or at night.
Traditionally, dynamic range of image sensors and displays has been confined to lower dynamic ranges of magnitude. Also, displays are often limited by viewing environment (they may render black if the luminance generation mechanism is switched off, but then they still reflect e.g. environmental light on their front glass; a television in sunny daytime viewing may have DR<50:1). Consequently, it has traditionally been possible to store and transmit images in 8-bit gamma-encoded formats without introducing perceptually noticeable artifacts on traditional rendering devices. However, in an effort to record more precise and livelier imagery, novel High Dynamic Range (HDR) image sensors that are capable of recording dynamic ranges of more than 6 orders of magnitude have been developed. Moreover, most special effects, computer graphics enhancement and other post-production work are already routinely conducted at higher bit depths and with higher dynamic ranges.
Furthermore, the contrast and peak luminance of state-of-the-art display systems continues to increase. Recently, new displays have been presented with a peak luminance as high as 4000 Cd/m−2 and contrast ratios of up to perhaps 5-6 orders of magnitude although this is typically reduced to significantly less in real life viewing environments. It is expected that future displays will be able to provide even higher dynamic ranges and specifically higher peak luminances and contrast ratios. When traditionally encoded 8-bit signals are displayed on such displays, annoying quantization and clipping artifacts may appear, or the grey values of the different regions may be incorrectly rendered, etc. Artefacts may be particularly noticeable if compression such as DCT compression according to an MPEG or similar still image or video compression standard is used somewhere along the imaging chain, from content creation to ultimate rendering. Moreover, traditional video formats offer insufficient headroom and accuracy to convey the rich information contained in new HDR imagery.
As a result, there is a growing need for new approaches that allow a consumer to fully benefit from the capabilities of state-of-the-art (and future) sensors and display systems. Preferably, representations of such additional information are backwards-compatible such that legacy equipment can still receive ordinary video streams, while new HDR-enabled devices can take full advantage of the additional information conveyed by the new format. Thus, it is desirable that encoded video data not only represents HDR images but also allow encoding of the corresponding traditional Low Dynamic Range (LDR) images that can be displayed on conventional equipment.
A critical issue for the introduction of increased dynamic range video and images is how to effectively encode, store, and distribute the associated information. In particular it is desirable that backwards compatibility is maintained, and that the introduction of high dynamic range images to existing systems is facilitated. Also efficiency in terms of data rate and processing complexity is significant. Another critical issue is of course the resulting image quality.
Hence, an improved approach for distributing, communicating and/or representing high dynamic range images would be advantageous.